In Matlab, generate two signals, 1[n] and x2[n], of 900 float elements each. The samples in a signal are the 9 digits in your student number, repeated 100 times. For example, if the first student number is "201338959", the first signal is x1[n]=(2, 0, 1, 3, 3, 8, 9, 5, 9, 2, 0, 1, 3, 3, 8, 9, 5, 9, 2, 0, 1, 3, 3, 8, 9, 5, 9, ...J. Signal 2[n] will be generated using the second student number. From each signal, subtract its mean value, so that the signal has zero mean. The sampling frequency to be used is equal to the mean between the values identified by the last four digits in both student numbers. For example, if the first student number is "201338959" and the second student number is "201343242", the sampling frequency to be used is round 8959+3242/2)=2034Hz. In those cases where the sampling frequency results in being less than 1000Hz, then 1000Hz should be added to it. In Matlab, plot time graphs of 3 cycles of each of the two signals generated; also plot frequency graphs of the two signals (using all 900 samples available for each), using 1024 points for the FFT. All plots should be fully and correctly labelled. For each of the two signals, use Matlab filterDesigner to design a bandstop FIR filter (pass band width of no more than 100Hz), with minimum order and with quantisation of coefficients to 32-bit floating point numbers, to remove the strongest component from the signal; the other components in the signal should not be affected significantly, i.e. they should not be distorted. If both signals have their strongest components in the same frequency, then the second strongest component in the second signal should be removed instead. In the report, provide the specifications of both filters, along with appropriately labelled time domain and frequency domain (both magnitude and phase) plots of the filters, and its pole-zero diagrams before and after quantisation. Filter the signals with the bandstop filters designed, generate time (3 cycles) and frequency (using all 900 samples, with 1024 FFT points) plots of the filtered signals and provide critical comments to these plots, to demonstrate that the filters work as intended and your understanding of the process. Export the filter coefficients to workspace from filter Designer, and make sure that such coefficients in the workspace are in single precision. Using the "save data.m" script provided as guidance, save numerator and denominator of the FIR filters as the two arrays "b_fir" and "a_fir", into a C-style header file "data.h".